Master-Thesis: “Exploring Cortical Ripples for Cognitive Enhancement” (Supervisors: Dr. Davide Ciliberti, Dr. Stefan Dürschmid, Dr. Christoph Reichert). We are looking for a highly motivated candidate with strong technical background (Biomedical engineering, Cognitive Psychology, Integrative Neuroscience, Data Science, Informatics, or similar fields), programming expertise (Python, Matlab or C++) and a keen interest in brain-computer interfacing and neural signal processing.
We offer the opportunity to discover the groundbreaking role of cortical ripples—brief bursts of neural activity essential for learning, memory consolidation, and decision-making. Until now, cortical ripples have been studied only through intracranial measurements in epilepsy patients. However, recent non-invasive magnetoencephalography (MEG) studies show ripple modulation after learning in the MTL region, allowing us to measure ripple dynamics in healthy participants on a larger scale. The goal of the project is to implement a real-time neurofeedback system based on ripples recorded in the medial temporal lobe via MEG. The system will serve to investigate the impact of cortical ripples on cognitive health. The position is supported by a HiWi salary (80h/month). Applications can be done by sending a CV to Dr. Davide Ciliberti ().

Master-Thesis: “Improving MR-based Multivariate Biomarker Classification using Multi-Site Harmonization” (Supervisor Dr. Gabriel Ziegler) We are looking for a highly motivated individual strong technical background with excellent grades (Biomedical engineering, Psychology, Integrative Neuroscience, Data Science), programming expertise (python) and deep interests in Bayesian statistics & AI to implement and test the effects of data harmonization (COMBAT) for MR-based classification of biomarker positivity (using kernel-methods).

Master-Thesis: “Improving MR-based Multivariate Memory Prediction using additional Vascular Imaging Modalities” (Supervisor Dr. Gabriel Ziegler) We are looking for a highly motivated individual strong technical background with excellent grades (Biomedical engineering, Psychology, Integrative Neuroscience, Data Science), programming expertise (python) and deep interests in Bayesian statistics & to implement and test the effects of incorporating additional vascular lesion-sensitive modalities (e.g. WMH/ePVS) into MR-based predictive modelling of memory performance (using Gaussian Processes).

Master-Thesis: “Improving MR-based Multivariate Biomarker Classification using Functional Imaging Data” (Supervisor Dr. Gabriel Ziegler) We are looking for a highly motivated individual strong technical background with excellent grades (Biomedical engineering, Psychology, Integrative Neuroscience, Data Science), programming expertise (python) and deep interests in Bayesian statistics & AI to implement and test the effects of incorporating additional functional task-based activity (fMRI-FADE) for MR-based classification of biomarker positivity (using kernel-methods).

Master-Thesis: “Improving MR-based Multivariate Memory Prediction using Hippocampal Subfield Segmentation” (Supervisor Dr. Gabriel Ziegler) We are looking for a highly motivated individual strong technical background with excellent grades (Biomedical engineering, Psychology, Integrative Neuroscience, Data Science), programming expertise (python) and deep interests in Bayesian statistics & AI to implement and test the effects of incorporating additional hippocampal subfield segmentations into MR-based predictive modelling of memory performance (using Gaussian Processes).

Master-Thesis: “MRI vascular lesion Analysis using Partial Least Squares in Alzheimer’s Disease” (Supervisor Dr. Gabriel Ziegler) We are looking for a highly motivated individual with strong technical background and excellent grades (Biomedical engineering, Psychology, Integrative Neuroscience, Data Science), programming expertise (python) and deep interests in statistics & machine learning to implement and apply multivariate analysis schemes (e.g. PLS and PCA) for analysis of vascular lesions (WMH and ePVS) in relation to lifestyle parameters.

Master-Thesis: “Multivariate MRI lesion mapping using Support Vector Machines in Alzheimer’s Disease” (Supervisor Dr. Gabriel Ziegler) We are looking for a highly motivated individual with strong technical background and excellent grades (Biomedical engineering, Psychology, Integrative Neuroscience, Data Science), programming expertise (python) and deep interests in statistics & machine learning to implement and apply multivariate analysis schemes (SVMs) for analysis of vascular lesions (WMH and ePVS).

Master-Thesis: “Large-scale MRI Image Processing in early Alzheimer’s Disease” (Supervisor Dr. Gabriel Ziegler) We are looking for a highly motivated individual with strong technical background and excellent grades (Biomedical engineering, Psychology, Integrative Neuroscience, Data Science), programming expertise and genuine interests in learning advanced image processing to implement longitudinal structural MRI feature pre-processing using large-scale ADNI database. 

We are offering an excellent agile, highly interdisciplinary research environment and computing infrastructure including strong dedication to supervision, teaching of state of the art research methods.If you have a high profile, care a lot about learning how to model data, and are genuinely interested in one of the above topics please notify (including the project title, CV, grades overview).